At what age does weight control become difficult?

Papers of particular interest, published recently, have been highlighted as:

• Of importance

•• Of major importance

1. Williamson DF, Kahn HS, Remington PL, Anda RF. The 10-year incidence of overweight and major weight gain in US adults. Arch Intern Med. 1990;150:665–672. doi: 10.1001/archinte.1990.00390150135026. [PubMed] [CrossRef] [Google Scholar]

2. Mokdad AH, Serdula MK, Dietz WH, Bowman BA, Marks JS, Koplan JP. The spread of the obesity epidemic in the United States, 1991–1998. JAMA. 1999;282:1519–1522. doi: 10.1001/jama.282.16.151. [PubMed] [CrossRef] [Google Scholar]

3. Muyle TP, Park MJ, Nelson CD, Adams SH, Irwin CE, Jr, Brindis CD. Trends in adolescent and young adult health in the United States. J Adolesc Health. 2009;45(1):8–24. doi: 10.1016/j.jadohealth.2009.03.013. [PubMed] [CrossRef] [Google Scholar]

4•. Truesdale KP, Stevens J, Lewis CE, Schreiner PJ, Loria CM, Cai J. Changes in risk factors for cardiovascular disease by baseline weight status in young adults who maintain or gain weight over 15 years: the CARDIA study. Int J Obes. 2016;30:1397–1407. doi: 10.1038/sj.ijo.0803307. Findings of this study underscore the importance of weight control in young adulthood: weight gained specifically during these years was associated with poorer cardiometabolic functioning 15 years later, regardless of initial weight status. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

5. Norman JE, Bild D, Lewis CE, Liu K, West DS, CARDIA Study The impact of weight change on cardiovascular disease risk factors in young black and white adults: The CARDIA study. Int J Obes Relat Metab Disord. 2003;27:369–376. doi: 10.1038/sj.ijo.0802243. [PubMed] [CrossRef] [Google Scholar]

6. Carnethon MR, Loria CM, Hill JO, Sidney S, Savage PJ, Liu K. Risk factors for the metabolic syndrome: the Coronary Artery Risk Development in Young Adults (CARDIA) study, 1985–2001. Diabetes Care. 2004;27:2707–2715. [PubMed] [Google Scholar]

7. Lloyd-Jones DM, Liu K, Colangelo LA, Yan LL, Klein L, Loria CM, et al. Consistently stable or decreased body mass index in young adulthood and longitudinal changes in metabolic syndrome components: the Coronary Artery Risk Development in Young Adults Study. Circulation. 2007;115:1004–1011. doi: 10.1161/circulationaha.106.648642. [PubMed] [CrossRef] [Google Scholar]

8. Merten MJ. Weight status continuity and change from adolescence to young adulthood: examining disease and health risk conditions. Obesity (Silver Spring) 2010;18:1423–1428. doi: 10.1038/oby.2009.365. [PubMed] [CrossRef] [Google Scholar]

9. Arnett JJ. Emerging adulthood: A theory of development from the late teens through the twenties. Am Psychol. 2000;55:469–480. doi: 10.1037/0003-066X.55.5.469. [PubMed] [CrossRef] [Google Scholar]

10. Roisman GI, Masten AS, Coatsworth JD, Tellegan A. Salient and emerging developmental tasks in the transition to adulthood. Child Dev. 2004;75:123–133. doi: 10.1093/acprof:oso/9780199736546.003.0. [PubMed] [CrossRef] [Google Scholar]

11. Arnett JJ. Emerging adulthood: The winding road from the late teens through the twenties. New York: Oxford University Press; 2004. [Google Scholar]

12. Arnett JJ. Adolescence and emerging adults: A cultural approach. 5th. Upper Saddle River: Pearson Education; 2013. [Google Scholar]

13. Arnett JJ. Clark University poll of emerging adults: Working, education, and identity. Clark University. 2015 www.clarku.edu/clark-poll-emerging-adults/pdfs/2015-clark-poll-report.pdf. Accessed 15 May 2017.

14. Geographical Mobility Database. United States Census Bureau. 2016 www.census.gov/data/tables/2016/demo/geographic-mobility/cps-2016.html. Accessed 15 May 2017.

15. Arnett JJ, Schwab J. The Clark University poll of emerging adults: Thriving, struggling, & hopeful. Clark University; 2012. //www2.clarku.edu/clark-poll-emerging-adults/pdfs/clark-university-poll-emerging-adults-findings.pdf. Accessed 15 May 2017. [Google Scholar]

16. Scott ME, Schelar E, Manlove J, Cui C. Young adult attitudes about relationships and marriage: Times may have changed but expectations remain high. Child Trends. 2009 //www.childtrends.org/wp-content/uploads/2009/07/Child_Trends-2009_07_08_RB_YoungAdultAttitudes.pdf. Accessed 15 May 2017.

17. Rauer AJ, Pettit GS, Lansford JE, Bates JE, Dodge KA. Romantic relationship patterns in young adulthood and their developmental antecedents. Dev Psychol. 2013;49:2159–2171. doi: 10.1037/a0031845. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

18. Gogtay N, Giedd JN, Lusk L, Hayashi KM, Greenstein D, Vaituzis AC, et al. Dynamic mapping of human cortical development during childhood through early adulthood. Proc Natl Acad Sci USA. 2004;101:8174–8179. doi: 10.1073/pnas.0402680101. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

19. Sowell ER, Thompson PM, Toga AW. Mapping changes in the human cortex throughout the span of life. Neuroscientist. 2004;10:372–392. doi: 10.1177/1073858404263960. [PubMed] [CrossRef] [Google Scholar]

20. Sowell ER, Thompson PM, Holmes CJ, Jernigan TL, Toga AW. In vivo evidence for post-adolescent brain maturation in frontal and striatal regions. Nat Neurosci. 1999;2:859–861. doi: 10.1038/13154. [PubMed] [CrossRef] [Google Scholar]

21. Vukman KB. Developmental Differences in Metacognition and their Connections with Cognitive Development in Adulthood. J Adult Dev. 2005;12:211–221. doi: 10.1007/s10804-005-7089-6. [CrossRef] [Google Scholar]

22. Johnson SB, Blum RW, Giedd JN. Adolescent maturity and the brain: the promise and pitfalls of neuroscience research in adolescent health policy. J Adolesc Health. 2009;45:216–221. doi: 10.1016/j.jadohealth.2009.05.016. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

23. Targeted approaches to weight control for young adults. National Institutes of Health; 2008. //grants.nih.gov/grants/guide/rfa-files/RFA-HL-08-007.html. Accessed 15 May 2017. [Google Scholar]

24. Loria CM, Signore C, Arteaga SS. The need for targeted weight-control approaches in young women and men. Am J Prev Med. 2010;38:233–235. doi: 10.1016/j.amepre.2009.11.001. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

25. National college health assessment II: Reference group executive summary. American College Health Association. 2011 //www.acha-ncha.org/docs/ACHA-NCHA-II_ReferenceGroup_ExecutiveSummary_Spring2011.pdf. Accessed 15 May 2017.

26. Duffey KJ, Gordon-Larsen P, Jacobs DR, Williams OD, Popkin BM. Differential associations of fast food and restaurant food consumption with 3-y change in body mass index: The Coronary Artery Risk Development in Young Adults Study. Am J Clin Nutr. 2007;85:201–208. [PubMed] [Google Scholar]

27. Niemeier HM, Raynor HA, Lloyd-Richardson EE, Rogers ML, Wing RR. Fast food consumption and breakfast skipping: Predictors of weight gain from adolescence to adulthood in a nationally representative sample. J Adolesc Health. 2006;39:842–849. doi: 10.1016/j.jadohealth.2006.07.001. [PubMed] [CrossRef] [Google Scholar]

28. Huffman L, West DS. Readiness to change sugar sweetened beverage intake among college students. Eat Behav. 2007:10–14. doi: 10.1016/j.eatbeh.2006.04.005. [PubMed] [CrossRef] [Google Scholar]

29. Results from the 2015 national survey on drug use and health. Substance Abuse and Mental Health Services Administration; 2016. //www.samhsa.gov/data/sites/default/files/NSDUH-DetTabs-2015/NSDUH-DetTabs-2015/NSDUH-DetTabs-2015.pdf. Accessed 15 May 2017. [Google Scholar]

30. Nelson MC, Story M, Larson NI, Neumark-Sztainer D, Lytle LA. Emerging adulthood and college-aged youth: An overlooked age for weight-related behavior change. Obesity (Silver Spring) 2008;16:2205–2211. doi: 10.1038/oby.2008.365. [PubMed] [CrossRef] [Google Scholar]

31. Physical activity. Healthy People 2020. www.healthypeople.gov/2020/topics-objectives/topic/physical-activity. Accessed 15 May 2017.

32. Caspersen CJ, Pereira MA, Curran KM. Changes in physical activity patterns in the United States, by sex and cross-sectional age. Med Sci Sports Exerc. 2000;32:1601–1609. doi: 10.1097/00005768-200009000-00013. [PubMed] [CrossRef] [Google Scholar]

33•. LaRose JG, Guthrie KM, Lanoye A, Tate DF, Robichaud E, Caccavale LJ, et al. A mixed methods approach to improving recruitment and engagement of emerging adults in behavioural weight loss programs. Obes Sci Pract. 2016;2:341–354. doi: 10.1002/osp4.71. This paper synthesizes results across 2 studies—one focus group study and one quantitative survey—and draws conclusions regarding effective methods for recruiting and engaging emerging adults age 18-25 in weight loss programs. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

34. Nelson MC, Kocos R, Lytle LA, Perry CL. Understanding the perceived determinants of weight-related behaviors in late adolescence: A qualitative analysis among college youth. J Nutr Educ Behav. 2009;41:287–292. doi: 10.1016/j.jneb.2008.05.005. [PubMed] [CrossRef] [Google Scholar]

35. Greaney ML, Less FD, White AA, Dayton SF, Riebe D, Blissmer B, et al. College students’ barriers and enablers for healthful weight management: A qualitative study. J Nutr Educ Behav. 2009;41:281–286. doi: 10.1016/j.jneb.2008.04.354. [PubMed] [CrossRef] [Google Scholar]

36. Maslowsky J, Ozer EJ. Developmental trends in sleep duration in adolescence and young adulthood: Evidence from a national United States sample. J Adolesc Health. 2014;54:691–7. doi: 10.1016/j.jadohealth.2013.10.201. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

37. Multiple jobholding over the past two decades. Bureau of Labor Statistics; 2015. //www.bls.gov/opub/mlr/2015/article/multiple-jobholding-over-the-past-two-decades-2.htm. Accessed 15 May 2017. [Google Scholar]

38. Vargas PA. The link between inadequate sleep and obesity in young adults. Curr Obes Rep. 2016;5:38–50. doi: 10.1007/s13679-016-0186-y. [PubMed] [CrossRef] [Google Scholar]

39. Marucci-Wellman HR, Lombardi DA, Willetts JL. Working multiple jobs over a day or a week: Short-term effects on sleep duration. Chronobiol Int. 2016;33:630–49. doi: 10.3109/07420528.2016.1167717. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

40. Steptoe A, Peacey V, Wardle J. Sleep duration and health in young adults. Arch Intern Med. 2006;166:1689–92. doi: 10.1001/archinte.166.16.1689. [PubMed] [CrossRef] [Google Scholar]

41. Hart CN, LaRose JG, Fava J, James B, Wing RR. The association between time in bed and obesity risk in young adults. Behav Sleep Med. 2013;11:321–327. doi: 10.1080/15402002.2012.700289. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

42. Jackson CL, Redline S, Emmons KM. Sleep as a potential fundamental contributor to disparities in cardiovascular health. Annu Rev Public Health. 2015;18:417–440. doi: 10.1146/annurev-publhealth-031914-122838. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

43. Spiegel K, Tasali E, Penev P, Van Cauter E. Brief communication: Sleep curtailment in healthy young men is associated with decreased leptin levels, elevated ghrelin levels, and increased hunger and appetite. Ann Intern Med. 2004;141:846–850. [PubMed] [Google Scholar]

44. Markwald RR, Melanson EL, Smith MR, Higgins J, Perreault L, Eckel RH, et al. Impact of insufficient sleep on total daily energy expenditure, food intake, and weight gain. Proc Natl Acad Sci USA. 2013;110:5695–5700. doi: 10.1073/pnas.1216951110. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

45. Ford ES, Li C, Wheaton AG, Chapman DP, Perry GS, Croft JB. Sleep duration and body mass index and waist circumference among U.S. adults. Obesity (Silver Spring) 2014;22:598–607. doi: 10.1002/oby.20558. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

46. Stress by generation. American Psychological Association; 2012. //www.apa.org/news/press/releases/stress/2012/generations.aspx. Accessed 15 May 2017. [Google Scholar]

47. Kessler RC, Walters EE. Epidemiology of DSM-III-R major depression and minor depression among adolescents and young adults in the National Comorbidity Survey. Depress Anxiety. 1998;7:3–14. [PubMed] [Google Scholar]

48. Major depression among adults. National Institute of Mental Health; 2015. www.nimh.nih.gov/health/statistics/prevalence/major-depression-among-adults.shtml. Accessed 15 May 2017. [Google Scholar]

49. Druss BG, Hoff RA, Rosenheck RA. Underuse of antidepressants in major depression: Prevalence and correlates in a national sample of young adults. J Clin Psychiatry. 2000;61:234–7. [PubMed] [Google Scholar]

50. Charmandari E, Tsigos C, Chrousos G. Endocrinology of the stress response. Annu Rev Physiol. 2005;67:259–284. doi: 10.1146/annurev.physiol.67.040403.120816. [PubMed] [CrossRef] [Google Scholar]

51. Torres SJ, Nowson CA. Relationship between stress, eating behavior, and obesity. Nutrition. 2007;23:887–894. doi: 10.1016/j.nut.2007.08.008. [PubMed] [CrossRef] [Google Scholar]

52. Swinburn B, Egger G, Raza F. Dissecting obesogenic environments: The development and application of a framework for identifying and prioritizing environmental interventions for obesity. Prev Med. 1999;29:563–570. doi: 10.1006/pmed.1999.0585. [PubMed] [CrossRef] [Google Scholar]

53. Forman E, Butryn M, Manasse S, Crosby R, Goldstein S, Wyckoff E, et al. Acceptance-based versus standard behavioral treatment for obesity: Results from the mind your health randomized controlled trial. Obesity (Silver Spring) 2016;24:2050–2056. doi: 10.1002/oby.21601. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

54. Corsica JA, Hood MM. Eating disorders in an obesogenic environment. J Am Diet Assoc. 2011;111:996–1000. doi: 10.1016/j.jada.2011.04.011. [PubMed] [CrossRef] [Google Scholar]

55. King BM. The modern obesity epidemic, ancestral hunter-gatherers, and the sensory/reward control of food intake. Amer Psychol. 2013;68:88–96. doi: 10.1037/a0030684. [PubMed] [CrossRef] [Google Scholar]

56. Anderson DA, Shapiro JR, Lundgren JD. The freshman year of college as a critical period for weight gain: An initial evaluation. Eat Behav. 2003;4:363–367. doi: 10.1016/S1471-0153(03)00030-8. [PubMed] [CrossRef] [Google Scholar]

57. Larson NI, Perry CL, Story M, Neumark-Sztainer D. Food preparation by young adults is associated with better diet quality. J Am Diet Assoc. 2006;106(12):2001–2007. [PubMed] [Google Scholar]

58. Back to school statistics. National Center for Education Statistics; //nces.ed.gov/fastfacts/display.asp?id=372. Accessed 15 May 2017. [Google Scholar]

59. Leahey TM, Gokee LaRose J, Fava JL, Wing RR. Social influences are associated with BMI and weight loss intentions in young adults. Obesity (Silver Spring) 2011;1:1157–1162. doi: 10.1038/oby.2010.301. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

60. Leahey TM, Doyle CY, Xu X, Bihuniak J, Wing RR. Social networks and social norms are associated with obesity treatment outcomes. Obesity (Silver Spring) 2015;23:1550–1554. doi: 10.1002/oby.21074. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

61. Fitzpatrick S, Gilbert S, Serpell L. Systematic review: Are overweight and obese individuals impaired on behavioural tasks of executive functioning? Neuropsychol Rev. 2013;23:138–156. doi: 10.1007/s11065-013-9224-7. [PubMed] [CrossRef] [Google Scholar]

62. Limbers CA, Young D. Executive functions and consumption of fruits/vegetables and high saturated fat foods in young adults. J Health Psychol. 2015;20:602–611. doi: 10.1177/1359105315573470. [PubMed] [CrossRef] [Google Scholar]

63. Hofmann W, Schmeichel BJ, Baddeley AD. Executive functions and self-regulation. Trends Cogn Sci. 2012;16:174–180. doi: 10.1016/j.tics.2012.01.006. [PubMed] [CrossRef] [Google Scholar]

64. Wing RR, Tate DF, Gorin AA, Raynor HA, Fava JL. A self-regulation program for maintenance of weight loss. N Engl J Med. 2006;355:1563–1571. doi: 10.1056/NEJMoa061883. [PubMed] [CrossRef] [Google Scholar]

65. Gokee-LaRose J, Gorin AA, Wing RR. Behavioral self-regulation for weight loss in young adults: a randomized controlled trial. Int JBehav Nutr Phys Act. 2009;6 doi: 10.1186/1479-5868-6-10. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

66. Lau JS, Adams SH, Boscardin WJ, Irwin CE., Jr Young adults’ health care utilization and expenditures prior to the Affordable Care Act. J Adolesc Health. 2014;54:663–671. doi: 10.1016/j.jadohealth.2014.03.001. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

67. Park MJ, Paul Mulye T, Adams SH, Brindis CD, Irwin CE., Jr The health status of young adults in the United States. J Adolesc Health. 2006;39:305–317. doi: 10.1016/j.jadohealth.2006.04.017. [PubMed] [CrossRef] [Google Scholar]

68. Fortuna RJ, Robbins BW, Halterman JS. Ambulatory care among young adults in the United States. Ann Intern Med. 2009;151:379–385. [PubMed] [Google Scholar]

69•. Committee on Improving the Health, Safety, and Well-Being of Young Adults; Board on Children, Youth, and Families; Institute of Medicine; National Research Council. The health care system. In: Bonnie RJ, Stroud C, Breiner H, editors. Investing in the health and well-being of young adults. Washington (DC): National Academies Press; p. 2015. This resource highlights health-related challenges unique to emerging adulthood and provides recommendations for intervention development and policy decisions. [Google Scholar]

70. Ozer EM, Urquhart JT, Brindis CD, Park MJ, Irwin CE., Jr Young adult preventive health care guidelines: There but can’t be found. Arch Pediatr Adolesc Med. 2012;166:240–247. doi: 10.1001/archpediatrics.2011.794. [PubMed] [CrossRef] [Google Scholar]

71. Antognoli EL, Smith KJ, Mason MJ, Milliner BR, Davis EM, Harris-Haywood S, et al. Direct observation of weight counselling in primary care: Alignment with clinical guidelines. Clin Obes. 2014;4:69–76. doi: 10.1111/cob.12050. [PubMed] [CrossRef] [Google Scholar]

72. Cole AM, Keppel GA, Andrilla HA, Cox CM, Baldwin LM, et al. Primary care patients’ willingness to participate in comprehensive weight loss programs. From the WWAMI region practice and research network. J Am Board Fam Med. 2016;29:572–580. doi: 10.3122/jabfm.2016.05.160039. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

73. Altieri MS, Tuppo C, Telem DA, Herlihy D, Cottell K, Pryor AD. Predictors of a successful medical weight loss program. Surg Obes Relat Dis. 2015;11:431–435. doi: 10.1016/j.soard.2014.09.019. [PubMed] [CrossRef] [Google Scholar]

74. Yoong SL, Carey M, Sanson-Fisher R, Grady A. A systematic review of behavioural weight-loss interventions involving primary-care physicians in overweight and obese primary-care patients (1999–2011) Public Health Nutr. 2013;16:2083–2099. doi: 10.1017/S1368980012004375. [PubMed] [CrossRef] [Google Scholar]

75. Booth HP, Prevost TA, Wright AJ, Gulliford MC. Effectiveness of behavioural weight loss interventions delivered in a primary care setting: A systematic review and meta-analysis. Fam Pract. 2014;31:643–653. doi: 10.1093/fampra/cmu064. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

76. Martin CK, Talamini L, Johnson A, Hymel AM, Khavjou O. Weight loss and retention in a commercial weight-loss program and the effect of corporate partnership. Int J Obes (Lond) 2010;34:742–50. doi: 10.1038/ijo.2009.276. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

77. Gudzune KA, Doshi RS, Mehta AK, Chaudhry ZW, Jacobs DK, Vakil RM, et al. Efficacy of commercial weight-loss programs: an updated systematic review. Ann Intern Med. 2015;162:501–512. doi: 10.7326/M14-2238. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

78. Hemmingsson E, Johansson K, Eriksson J, Sundström J, Neovius M, Marcus C. Weight loss and dropout during a commercial weight-loss program including a very-low-calorie diet, a low-calorie diet, or restricted normal food: Observational cohort study. Am J Clin Nutr. 2012;96:953–961. doi: 10.3945/ajcn.112.038265. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

79. LaRose JG, Leahey TM, Hill JO, Wing RR. Differences in motivations and weight loss behaviors in young adults and older adults in the National Weight Control Registry. Obesity (Silver Spring) 2013;21:449–453. doi: 10.1002/oby.20053. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

80. Gokee-LaRose J, Gorin AA, Raynor HA, Laska MN, Jeffery RW, Levy RL, et al. Are standard behavioral weight loss programs effective for young adults? Int J Obes (Lond) 2009;33:1374–1380. doi: 10.1038/ijo.2009.185. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

81. Coday M, Richey P, Thomas F, Tran QT, Terrell SB, Tylavsky F, et al. The recruitment experience of a randomized clinical trial to aid young adult smokers to stop smoking without weight gain with interactive technology. Contemp Clin Trials Commun. 2016;15:61–68. doi: 10.1016/j.conctc.2015.12.010. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

82. Jakicic JM, King WC, Marcus MD, Davis KK, Helsel D, Rickman AD, et al. Short-term weight loss with diet and physical activity in young adults: The IDEA study. Obesity (Silver Spring) 2015;23:2385–2397. doi: 10.1002/oby.21241. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

83. Fernandez ID, Groth SW, Reschke JE, Graham ML, Strawderman M, Olson CM. eMoms: Electronically-mediated weight interventions for pregnant and postpartum women. Study design and baseline characteristics. Contemp Clin Trials. 2015;43:63–74. doi: 10.1016/j.cct.2015.04.013. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

84. Corsino L, Lin PH, Batch BC, Intille S, Grambow SC, Bosworth HB, et al. Recruiting young adults into a weight loss trial: report of protocol development and recruitment results. Contemp Clin Trials. 2013;35:1–7. doi: 10.1016/j.cct.2013.04.002. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

85. Tate DF, LaRose JG, Griffin LP, Erickson KE, Robichaud EF, Perdue L, et al. Recruitment of young adults into a randomized controlled trial of weight gain prevention: Message development, methods, and cost. Trials. 2014;15 doi: 10.1186/1745-6215-15-326. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

86. Patrick K, Marshall SJ, Davila EP, Kolodziejczyk JK, Fowler JH, Calfas KJ, et al. Design and implementation of a randomized controlled social and mobile weight loss trial for young adults (project SMART) Contemp Clin Trials. 2014;37:10–18. doi: 10.1016/j.cct.2013.11.001. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

87. Moe SG, Lytle LA, Nanney MS, Linde JA, Laska MN. Recruiting and retaining young adults in a weight gain prevention trial: Lessons learned from the CHOICES study. Clin Trials. 2016;13:205–213. doi: 10.1177/1740774515605084. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

88. Poobalan AS, Aucott LS, Precious E, Crombie IK, Smith WC. Weight loss interventions in young people (18 to 25 year olds): A systematic review. Obes Rev. 2010;11:580–592. [PubMed] [Google Scholar]

89. LaRose JG, Tate DF, Lanoye A, Fava JL, Jelalian E, Blumenthal M, et al. Adapting evidence-based behavioral weight loss programs for emerging adults: A pilot randomized controlled trial. J Health Psychol. 2017 doi: 10.1177/1359105316688951. epub ahead of print. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

90. Linde JA, Sevcik SM, Petrich CA, Gardner JK, Laska MN, Lozano P, et al. Translating a health behavior change intervention for delivery to 2-year college students: The importance of formative research. Transl Behav Med. 2014;4:160–169. doi: 10.1007/s13142-013-0243-y. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

91. Gupta A, Calfas KJ, Marshall SJ, Robinson TN, Rock CL, Huang JS, et al. Clinical trial management of participant recruitment, enrollment, engagement, and retention in the SMART study using a Marketing and Information Technology (MARKIT) model. Contemp Clin Trials. 2015;42:185–195. doi: 10.1016/j.cct.2015.04.002. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

92. LaRose JG, Gorin AA, Bean MK, Lanoye A, Fava JL, Robinson EM, et al. Using motivational interviewing to enhance engagement in a weight loss program targeting emerging adults: Findings from a randomized controlled pilot trial. Poster presentation at The Obesity Society Annual Meeting; 2016; New Orleans, LA. [Google Scholar]

93. Merchant G, Weibel N, Pina L, Griswold WG, Fowler JH, Ayala GX, et al. Face-to-face and online networks: College students’ experiences in a weight loss trial. J Health Commun. 2017;22:75–83. doi: 10.1080/10810730.2016.1250847. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

94•. Godino JG, Merchant G, Norman GJ, Donohue MC, Marshall SJ, Fowler JH, et al. Using social and mobile tools for weight loss in overweight and obese young adults (Project SMART): A 2 year, parallel-group, randomised, controlled trial. Lancet Diabetes Endocrinol. 2016;4:747–755. doi: 10.1016/S2213-8587(16)30105-X. Project SMART is one of seven EARLY trials targeting weight control in young adults age 18–35. This paper presents main outcomes from their randomized controlled trial testing technology-based delivery of a weight loss intervention among college students. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

95. Gokee LaRose J, Leahey TM, Weinberg BM, Kumar R, Wing RR. Young adults’ performance in a low-intensity weight loss campaign. Obesity (Silver Spring) 2012;20:2314–2316. doi: 10.1038/oby.2012.30. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

96•. Svetkey LP, Batch BC, Lin PH, Intille SS, Corsino L, Tyson CC, et al. Cell phone intervention for you (CITY): A randomized, controlled trial of behavioral weight loss intervention for young adults using mobile technology. Obesity (Silver Spring) 2015;23:2133–2141. doi: 10.1002/oby.21226. CITY is another EARLY trial testing a technology-based delivery method for weight loss in young adults. This paper presents findings from their randomized controlled trial comparing an entirely technology-mediated intervention to one delivered in-person and supplemented with technology (i.e., smartphone self-monitoring) [PMC free article] [PubMed] [CrossRef] [Google Scholar]

97•. Jakicic JM, Davis KK, Rogers RJ, King WC, Marcus MD, Helsel D, et al. Effect of wearable technology combined with a lifestyle intervention on long-term weight loss: The IDEA randomized clinical trial. JAMA. 2016;316:1161–1171. doi: 10.1001/jama.2016.12858. IDEA is also one of the EARLY trials targeting weight loss in young adults. Investigators developed an intervention delivered first in-person, then via intervention website, text messages, and brief phone calls. Randomly assigned participants were given a wearable physical activity tracker. This paper presents main outcome findings 2 years post-baseline. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

98. Lytle LA, Moe SG, Nanney MS, Laska MN, Linde JA. Designing a weight gain prevention trial for young adults: The CHOICES study. Am J Health Educ. 2014;45:67–75. doi: 10.1080/19325037.2013.875962. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

99•. Lytle LA, Laska MN, Linde JA, Moe SG, Nanney MS, Hannan PJ, et al. Weight-gain reduction among 2-year college students: The CHOICES RCT. Am J Prev Med. 2017;52:183–191. doi: 10.1016/j.amepre.2016.10.012. The CHOICES trial, also part of the EARLY Consortium, targeted 2-year college students for weight gain prevention via a one-credit college course (offered in-person, online, or in combination) followed by a social networking and support website. This paper presents the main outcomes from the CHOICES trial. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

100. Laska MN, Sevcik SM, Moe SG, Petrich CA, Nanney MS, Linde JA, et al. A 2-year young adult obesity prevention trial in the US: Process evaluation results. Health Promot Int. 2016;31:793–800. [PMC free article] [PubMed] [Google Scholar]

101. Wing RR, Tate D, Espeland M, Gorin A, LaRose JG, Robichaud EF, et al. Weight gain prevention in young adults: Design of the study of novel approaches to weight gain prevention (SNAP) randomized controlled trial. BMC Public Health. 2013;13:300. doi: 10.1186/1471-2458-13-300. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

102•. Wing RR, Tate DF, Espeland MA, Lewis CE, LaRose JG, Gorin AA, et al. Innovative self-regulation strategies to reduce weight gain in young adults: The Study of Novel Approaches to Weight Gain Prevention (SNAP) randomized clinical trial. JAMA Intern Med. 2016;176:755–762. doi: 10.1001/jamainternmed.2016.1236. The SNAP Trial was also included in the EARLY Trials Consortium. Investigators developed two interventions to minimize weight gain in young adulthood: their large-changes approach aimed to induce weight loss to buffer against future weight gain, while their small-changes approach focused on small, daily changes to promote energy imbalance. This paper presents outcomes of both interventions compared to control over an average of 3 years of follow up. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

103. Leahey TM, LaRose JG, Lanoye A, Fava JF, Wing RR. Secondary data analysis from a randomized trial examining the effects of small financial incentives on intrinsic and extrinsic motivation for weight loss. Health Psychol Behav Med. Forthcoming. [Google Scholar]

104. LaRose JG, Wing RR. Lifestyle approaches to obesity treatment. In: Rios MS, Ordovas LM, Gutierrez Fuentes JA, editors. Obesity. Barcelona, Spain: Elsevier; 2011. pp. 311–22. [Google Scholar]

105. Wing RR, Tate D, LaRose JG, Gorin AA, Erickson K, Robichaud EF, et al. Frequent self-weighing as part of a constellation of healthy weight control practices in young adults. Obesity (Silver Spring) 2015;23:943–949. doi: 10.1002/oby.21064. [PMC free article] [PubMed] [CrossRef] [Google Scholar]

106. LaRose JG, Lanoye A, Tate DF, Wing RR. Frequency of self-weighing and weight loss outcomes within a brief lifestyle intervention targeting emerging adults. Obes Sci Pract. 2016;2:88–92. [PMC free article] [PubMed] [Google Scholar]

107. Napolitano MA, Hayes S, Bennett GG, Ives AK, Foster GD. Using Facebook and text messaging to deliver a weight loss program to college students. Obesity (Silver Spring) 2013;21:25–31. doi: 10.1002/oby.20232. [PubMed] [CrossRef] [Google Scholar]

108. Flegal KM, Carroll MD, Kit BK, Ogden CL. Prevalence of obesity and trends in the distribution of body mass index among US adults, 1999–2010. JAMA. 2012;307:491–497. [PubMed] [Google Scholar]

Page 2

TrialSample CharacteristicsInterventionMain Outcomes
aChoosing Healthy Options in College Environments & Settings (CHOICES)87,90,98–100N=44167.6% female72.6% white100% student (2-year college)

Age= 22.7 (5.0)b


BMI = 25.4 (3.8)b
24-month weight gain prevention interventionIntervention: 1-credit college course + intervention website with social support, resources, and self-monitoring platform

Control: Quarterly health promotion information

No difference in BMI, weight, waist circumference, or body fat percentage between intervention and control at 24 months

Significant reduction in prevalence of BMI ≥ 25 in intervention compared to control at 24 months

Cell Phone Intervention for You (CITY)84,96N=36569.6% female56.2% white34.3% student

Age = 29.4 (4.3)b


BMI = 35.2 (7.8)b
24-month weight loss interventionIntervention 1 (CP): Comprehensive interactive cell phone app used for both intervention delivery and self-monitoringIntervention 2 (PC): Delivered via group sessions and personal coaching; self-monitoring via smartphone

Control: Provided 3 handouts on healthy eating and physical activity

No difference in weight loss between groups at 24 months

Significantly greater weight losses in PC compared to both CP and Control at 6 and 12 months

eMoms83N=1689 (ITT)100% pregnant women68.0% white[student status not reported]

Age = 27.5 (4.7)b


BMI = 25.4 (4.3)b
See footnotedSee footnoted
Innovative Approaches to Diet, Exercise, and Activity (IDEA)82,97N=47171.1% female77.2% white25.7% student

Age = 30.9 (27.8–33.7)c


BMI = 31.2 (28.4–34.3)c
24-month weight loss interventionIntervention 1 (Standard): in-person group behavioral weight loss + phone counseling/study website; self-monitoring via website

Intervention 2 (Enhanced): in-person group behavioral weight loss + phone counseling/study website; self-monitoring via provided wearable device + web platform

No difference in body composition, physical activity, or dietary behaviors between groups

Significantly greater weight losses in Standard compared to Enhanced at 12, 18, & 24 months

Study of Novel Approaches to Weight Gain Prevention (SNAP)85,101–102N=59978.3% female73.1% white24.3% student (full-time)

Age = 28.2 (4.4)b

26.2% age 18–24.9

BMI = 25.4 (2.6)b

4-month weight gain prevention intervention with low-intensity follow-up (average 3 years)Intervention 1 (SC): 10 group in-person sessions followed by online weight reporting with feedback and quarterly online refreshers; instructed to make small, daily changes to eating and activityIntervention 2 (LC): 10 group in-person sessions followed by online weight reporting with feedback and quarterly online refreshers; instructed to make large changes initially to produce weight loss of 5–10lbs to create buffer against future gains

Control: 1 group in-person meeting providing an overview of both SC and LC approaches

Significantly greater weight losses in both LC and SC compared to Control at primary endpoint (average follow up of 3 years); significantly greater weight losses in LC compared to SC at primary endpoint
aSocial Mobile Approaches to Reduce Weight (Project SMART)86,91,93–94N=40470.3% female41.8% white100% student

Age = 22.7 (3.8)b


BMI = 29.0 (2.8)b
24-month weight loss interventionIntervention: Delivery across multiple channels: Facebook, mobile apps, website, email, text, & health coaching

Control: Access to general health education website without social networking components

No difference in weight loss between intervention and control at 24 months

Significantly greater weight loss in intervention at 6 and 12 months compared to control

Treating Adults at Risk for Weight Gain with Interactive Technology (TARGIT)81N=33048.8% female57.3% white[student status not reported]100% current smokers

Age = 29.7 (4.2)b

BMI < 25: 23.0%25–29.9: 37.6%

30+: 39.4%

See footnotedSee footnoted

Última postagem

Tag